New normalization index for spontaneous imbibition

Abstract

Spontaneous imbibition is of special importance in oil recovery from fractured reservoirs. Laboratory measurements of volume of liquid imbibed versus time are often used in the prediction of oil recovery. Laboratory results of oil recovery through spontaneous imbibition are commonly scaled-up to forecast oil recovery at the reservoir scale. Numerous questions arise with respect to the theory of spontaneous imbibition and the valid scaling of laboratory imbibition data. The factors involved in the scaling equation are rock properties, liquids viscosities, interfacial tensions, core geometry and wettability. Some previous developments in scaling were based on oil recovery from very strongly water-wet rocks. In this paper, sequential developments in the mathematical analysis of scaling equations for imbibition recovery are reviewed to the latest one. Previous scaling equations do not fit the imbibition data with different wettabilities in cores. To show this fact, two series of experiments are done on water wet and oil wet cores. Oil wet cores are obtained by means of aging process. The effect of interfacial tension is considered using a new type of surfactant. Imbibition data is compared with different scaling equations that are available in the literature for providing a physical explanation of the new index. The results reveal the inconsistency between scaling equations. Previous methods did not consider the effects of all parameters on determining the Wettability Index. A new procedure is introduced in order to obtain the Normalization Index from the imbibition data using all the parameters affecting the imbibition rate, including wettability. This index, which could be considered as a substitute for the Wettability Index, is then used to modify previous scaling equations and called the Normalization Index. The improved correlation is shown to perform better than the existing equations available in the literature as it gives the closest fit to the experimental data.